WISRAN

Wisran is a revolutionary startup idea, selected by MIT boot camp. It uses data science to measure time variations of farming.

CHALLENGES

Limited time and budget

Provided with all of its complexity, we had to prove our idea, by developing a minimum viable product, within a season, i.e. 3 months as we didn’t have enough budget to record data of whole year farming cycle covering all processes and seasons.

Real-time activity mapping

As different industrial farming vehicles, each having different sizes, speed and movement actions were involved even in a single process, identification of current activity was dependent on many variables. We had to develop a rule engine for analyzing a broad set of variables and determining current activity and its relative stage.

Scalability

Scalability was a real challenge as adding a single node in the system adds a huge volume of data. We had to design a decoupled architecture that keeps all software components, along the data pipeline and data aggregation engine in their optimally efficient state and ensures the analysis, aggregation, and computation on a vast set of data provides a real-time picture.

Complex Business Domain

RESULTS

Wisran is live with an Android and an iOS app. It has now successfully automated 56713 acres of industrial agriculture fields and made its way to Australia by winning a grant from the Australian government.

SOLUTIONS

Limited time and budget

Our years-long experience of managing medium and large complex projects helped us in keeping this project on its planned trajectory. We followed Agile processes and divided relevant stories in sprints with complete focus on adding maximum business value in each sprint.

Real-time activity mapping

We used Apache Kafka and Nifi to receive and channelize data streams, being relayed towards our rule engine powered by Apache spark, that analyzed and made aggregations based on complex rules at high speed.

Scalability

The decoupled infrastructure design rescued us. We designed the system in three layers: a data pipeline, a core engine, and a data layer. Each of these layers is a multi-node system, and we can add multiple nodes in each layer according to the system demand, anytime.

Complex Business Domain

Our onsite manager visited the original site and conducted dozens of interviews with clients, business stakeholders and vehicle operators. Various interactive meetings and brainstorming sessions were held. With the well-organized collaborative effort, we were able to convert business requirements to stories and epics.

Equipment Monitoring:

It helps to remotely check the mixed fleet of various models of trucks and other equipment.

Automated Guidance:

Automated guidance related to the inefficiency of the field is provided to offer more jobs in less time.

Analysis of Financial Impact:

WISRAN uses technology for analyzing the financial effects of fieldwork performance.

Maximum Profit:

The actual time and cost per acre are tracked to get the maximum profit.

key features
Technology stack

Development

ios

  Swift 4

Android

Kotlin/Java 7

Backend

Web (Admin panel)

    Ruby on Rails

     Google Map API

    Apache Spark

      Apache Kafka

       Postgres DB

     Apache NIFI

   Postgres GIS

Testing

Jira

 Confluence

 Bitbucket

Jenkins

Crashlytics

Production

Production server:

AWS

EC2

S3

  Apple Store

Wisran Review

Arslan Lodhi
C.E.O Wisran

Salman and team at Clustox has always gone beyond what was asked. Their differentiation is that they come back with great ideas to enhance user experience and product improvements.

Do you want to get anything like that?

 

 

Do you want to get anything like that?